A new chiller fault diagnosis method under the imbalanced data environment via combining an improved generative adversarial network with an enhanced deep extreme learning machine

Engineering Applications of Artificial Intelligence, Год журнала: 2024, Номер 137, С. 109218 - 109218

Опубликована: Авг. 31, 2024

Язык: Английский

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A review on convolutional neural network in rolling bearing fault diagnosis

Measurement Science and Technology, Год журнала: 2024, Номер 35(7), С. 072002 - 072002

Опубликована: Март 19, 2024

Abstract The health condition of rolling bearings has a direct impact on the safe operation rotating machinery. And their working environment is harsh and complex, which brings challenges to fault diagnosis. With development computer technology, deep learning been applied in field diagnosis rapidly developed. Among them, convolutional neural network (CNN) received great attention from researchers due its powerful data mining ability feature adaptive ability. Based recent research hotspots, history trend CNN summarized analyzed. Firstly, basic structure introduced important progress classical models for bearing years studied. problems with classic algorithm have pointed out. Secondly, solve above problems, combined achievements, various methods principles optimizing are compared perspectives extraction, hyperparameter optimization, optimization. Although significant made based CNN, there still room improvement addressing issues such as low accuracy imbalanced data, weak model generalization, poor interpretability. Therefore, future networks discussed finally. transfer improve generalization interpretable used increase interpretability networks.

Язык: Английский

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Chiller energy prediction in commercial building: A metaheuristic-Enhanced deep learning approach

Energy, Год журнала: 2024, Номер 297, С. 131159 - 131159

Опубликована: Апрель 4, 2024

Язык: Английский

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An interpretable graph convolutional neural network based fault diagnosis method for building energy systems

Building Simulation, Год журнала: 2024, Номер 17(7), С. 1113 - 1136

Опубликована: Июнь 20, 2024

Язык: Английский

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Enhancing Reliability Through Interpretability: A Comprehensive Survey of Interpretable Intelligent Fault Diagnosis in Rotating Machinery

IEEE Access, Год журнала: 2024, Номер 12, С. 103348 - 103379

Опубликована: Янв. 1, 2024

This paper presents a comprehensive survey on interpretable intelligent fault diagnosis for rotating machinery, addressing the challenge of "black box" nature machine learning techniques that hampers reliability in automated diagnostic processes. It underscores growing importance interpretability (IFD), marking shift from traditional signal processing methods to learning-based approaches necessitate transparency trustworthiness. Our review systematically collates and examines spectrum IFD, distinguishing between post-hoc ante-hoc strategies. We detail mainstream methods, their applications, critique limitations, particularly absence physical significance. The then explores incorporate knowledge upfront, enhancing interpretability. By categorizing evaluating three distinct embedding approaches, we shed light unique applications. Conclusively, highlight emerging research directions challenges field, aiming equip readers with nuanced understanding current methodologies inspire future studies making IFD more reliable interpretable.

Язык: Английский

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An enhanced digital twin-driven fault detection and isolation method based on sensor series imaging mechanism for gas turbine engine

Applied Thermal Engineering, Год журнала: 2024, Номер 257, С. 124308 - 124308

Опубликована: Сен. 2, 2024

Язык: Английский

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Interpretability assessment of convolutional neural network-based fault diagnosis for air handling units working in three seasons

Energy and Buildings, Год журнала: 2024, Номер unknown, С. 114876 - 114876

Опубликована: Окт. 1, 2024

Язык: Английский

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A metro train air conditioning system fault diagnosis method based on explainable artificial intelligence: Considering interpretability and generalization

International Journal of Refrigeration, Год журнала: 2025, Номер unknown

Опубликована: Март 1, 2025

Язык: Английский

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Customized large-scale model for human-AI collaborative operation and maintenance management of building energy systems

Applied Energy, Год журнала: 2025, Номер 393, С. 126169 - 126169

Опубликована: Май 20, 2025

Язык: Английский

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Advanced fault detection, diagnosis and prognosis in HVAC systems: Lifecycle insight, key challenges, and promising approaches

Renewable and Sustainable Energy Reviews, Год журнала: 2025, Номер 219, С. 115867 - 115867

Опубликована: Май 27, 2025

Язык: Английский

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